## `summarise()` has grouped output by 'patient', 'age_at_sample_exact', 'age_at_sample', 'DOB', 'DATE_OF_DIAGNOSIS'. You can override using the `.groups` argument.
## Joining, by = "PDID"
| patient | ID | age_at_sample_exact | cell_type | phase | BaitLabel | |
|---|---|---|---|---|---|---|
| 3 | PD6646 | PD6646n | 76.44353 | PB Gran | Recapture | PD6646n |
| 4 | PD6646 | PD6646o | 78.97331 | PB Gran | Recapture | PD6646o |
| 5 | PD6646 | PD6646p | 80.14237 | PB Gran | Recapture | PD6646p |
| 1 | PD6646 | COLONY81 | 81.01027 | BFU-E-Colony | Colony | NA |
| 6 | PD6646 | PD6646q | 82.97878 | PB Gran | Recapture | PD6646q |
| 2 | PD6646 | COLONY85 | 84.70089 | BFU-E-Colony | Colony | NA |
tree=plot_basic_tree(PD$pdx,label = PD$patient,style="classic")
The nodes in this plot can be cross-referenced with nodes specified in subsequent results. The plot also serves to give an idea of what the topology at the top of the tree looks like.
tree=plot_basic_tree(expand_short_branches(PD$pdx,prop = 0.1),label = PD$patient,style="classic")
node_labels(tree)
Note that the different colours on the tree indicate the separately fitted mutation rate clades.
##
## Random-Effects Model (k = 1; tau^2 estimator: REML)
##
## logLik deviance AIC BIC AICc
## 0.0000 -0.0000 4.0000 -Inf 16.0000
##
## tau^2 (estimated amount of total heterogeneity): 0
## tau (square root of estimated tau^2 value): 0
## I^2 (total heterogeneity / total variability): 0.00%
## H^2 (total variability / sampling variability): 1.00
##
## Test for Heterogeneity:
## Q(df = 0) = 0.0000, p-val = 1.0000
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## 19.3909 0.6033 32.1417 <.0001 18.2085 20.5734 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## `summarise()` has grouped output by 'patient'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'patient'. You can override using the `.groups` argument.
| node | driver | status | child_count | type | colony_count | mean_lambda_rescaled | correction | sd_rescaled | lb_rescaled | ub_rescaled | median_rescaled | p_lt_wt |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| -1 | WT | 1 | -1 | local | 18 | 19.39092 | 1.014996 | 0.3639650 | 18.69665 | 20.12276 | 19.38593 | NA |
| 121 | DNMT3A | 1 | 99 | local | 8 | 18.68510 | 1.014996 | 0.4727588 | 17.79205 | 19.65477 | 18.67391 | 0.870800 |
| 142 | JAK2:DNMT3A | 1 | 77 | local | 73 | 22.60973 | 1.014996 | 1.5523421 | 19.71770 | 25.75073 | 22.56640 | 0.016100 |
| 175 | 9pUPD:JAK2:DNMT3A | 0 | 3 | local | 3 | 25.39854 | 1.014996 | 1.9432401 | 21.78597 | 29.39981 | 25.33098 | 0.000375 |
| 27 | 9pUPD:JAK2:DNMT3A | 0 | 1 | local | 1 | 21.37484 | 1.014996 | 3.8666001 | 12.74849 | 28.33233 | 21.68363 | 0.266800 |
| 124 | CBL:DNMT3A | 1 | 14 | local | 14 | 18.26586 | 1.014996 | 0.7048151 | 16.92716 | 19.71524 | 18.24567 | 0.914675 |
All ages are in terms of post conception years. The vertical red lines denote when colonies were sampled and blue lines when targeted follow up samples were taken.
| patient | node | driver | child_count | lower_median | upper_median | lower_lb95 | lower_ub95 | upper_lb95 | upper_ub95 | N | group | age_at_diagnosis_pcy | max_age_at_sample | min_age_at_sample |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PD6646 | 121 | DNMT3A | 99 | 0.0110787 | 27.17183 | 0.0082774 | 0.0254408 | 24.99919 | 29.40281 | 6 | DNMT3A | 76.80767 | 85.42916 | 77.1718 |
| PD6646 | 124 | CBL | 14 | 32.1642463 | 50.72960 | 29.9563203 | 34.4032654 | 48.41968 | 52.95501 | 6 | CBL | 76.80767 | 85.42916 | 77.1718 |
| PD6646 | 142 | JAK2 | 77 | 29.6007868 | 63.17088 | 27.4336204 | 31.8099078 | 60.35690 | 65.61309 | 6 | JAK2 | 76.80767 | 85.42916 | 77.1718 |
| PD6646 | 175 | 9pUPD | 3 | 67.3874939 | 72.79130 | 65.1055774 | 69.3451450 | 71.02458 | 74.30215 | 6 | 9pUPD | 76.80767 | 85.42916 | 77.1718 |
## Timings using the Clade Specific Rates
| label | node | het.sensitivity | chr | start | end | nhet | nhom | mean_loh_event | lower_loh_event | upper_loh_event | t_before_end | t_before_end_lower | t_before_end_upper | kb | count_in_bin | count_se | pmut | pmut_se | xmean | xse_mean | xsd | x2.5. | x50. | x97.5. | xn_eff | xRhat | lmean | lse_mean | patient | driver3 | child_count |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 9pUPD_A | 175 | 0.9629 | 9 | 10469 | 5464376 | 0 | 0 | 70.26 | 67.53 | 72.64 | 2.497 | 0.1131 | 5.23 | 5400000 | 838 | 28.95 | 0.00183 | 6.322e-05 | 0.5387 | 0.002153 | 0.2867 | 0.0336 | 0.5591 | 0.9791 | 17730 | 1 | 1.000 | 4.126e-07 | PD6646 | 9pUPD:JAK2:DNMT3A | 3 |
| 9pUPD_B | 27 | 0.7240 | 9 | 10469 | 33800406 | 1 | 2 | NA | NA | NA | NA | NA | NA | 33800000 | 6732 | 82.05 | 0.01470 | 1.792e-04 | 0.6540 | 0.001191 | 0.1897 | 0.2448 | 0.6774 | 0.9478 | 25378 | 1 | 6.447 | 4.901e-04 | NA | NA | NA |
Here we exclude all local CNAs and depict as color VAF plots